Kohli, D.

Kuffer, M.

Nagenborg, Michael Herbert

Persello, C.

Pfeffer, K.

Sliuzas, R.V.

Wang, Jiong

English

University of Twente Research Information

PROSPECTS FOR GLOBAL MONITORING OF THE SDG SLUM INDICATOR WITH EARTH OBSERVATIONSLIUZAS, R., KUFFER, M., WANG, J., NAGENBORG, M., PFEFFER, K., KOHLI, D., AND PERSELLO, C.CONTENTS Some basic parameters for slum mapping (with EO) Slum mapping research at ITC Prospects and issues for global slum mappingWho are slums dwellers?Urban households lacking at least 1 of the following: Adequate water  Adequate sanitation Sufficient living space Secure tenure Durable housing (quality of structures & environment – hazards)Large scale surveys: Census, DHSCity and Settlement surveysThe nature of slum dwellers and slumsUN-HABITAT 2002INDICATORS FOR SLUM DWELLERSADEQUATE WATER AND ADEQUATE SANITATIONTENURE SECURITY OVERCROWDING> 3 persons per roomDURABLE HOUSINGPRIVATE VS PUBLIC SPACE, BUILDING AND PLANNING STANDARDSDURABLE HOUSING:SAFE FROM NATURAL AND TECHNOLOGICAL HAZARDSvoiceofglobalummah.blogspot.comHAZARDS AND SLUM FORMATION: DAR ES SALAAMINFORMAL VS FORMAL URBAN DEVELOPMENT12345  Vacant land                               S C  O  OC SS STime Vacant landFormalInformalPlanningServicingBuildingOccupationMonitor planimplementationOccupation (land)BuildingServicingPlanning(regularization, eviction, resettlement)Monitor (guide) citizen leddevelopmentAdapted from BarosSliuzas et al., 2017 https://ieeexplore.ieee.org/document/7924589SLUMS: spatial concentration of slum dwellers -diversity of physical forms and settingsKisumu KenyaCairoEgyptAhmedabadIndiaKampalaUgandaTHE URBAN DIVIDE – THE MORPHOLOGYMORPHOLOGY OF SLUMS – FROM SPACEFeatures Slums Planned areasSize • Small building sizes • Generally larger building sizesDensity • High densities (roof coverage)• Lack of public (green) spaces• Low – moderate density areas• Provision of public (green spaces)Pattern • Organic layout structure • Regular layout patternSite Aspects • Hazardous locations• Access to livelihood opportunities• Etc…• Formal development with services and infrastructure provisionWhat is specific to slums?53 Richard Sliuzas#SFAP4_18 #SFAP4_16#SFAP4_11#SFAP4_06#SFAP3_36 #SFAP3_30#SFAP3_29#SFAP3_23 #SFAP3_22#SFAP3_17 (Source: Sliuzas, 2004)SLUM MAPPING FROM SMALL FORMAT AERIAL PHOTOSPOINT CLOUD FROM UAV IMAGES, KIGALI, RWANDAFOR 2D AND 3D ANALYSIS AND PLANNING(IMAGE BY C. GEVAERT)THE URBAN DIVIDEWhat do we know about global slum developments 15 years of slum mapping using remote sensing(Kuffer, Pfeffer and Sliuzas, 2016) Based on 87 publications selected and reviewedTHE GENERIC SLUM ONTOLOGY Kohli, D.; Sliuzas, R.V.; Kerle, N.; Stein, A. An ontology of slums for image-based classification. Comput. Environ. Urban Syst. 2012, 36, 154–163.Environs Settlement Base ObjectBuilding CharacteristicsRoad LayoutShapeDensityNeighborhood CharacteristicsLocationSpatial orderDIFFERENCESSLUM MAPPINGACCURACIES OF METHODS TO MAP SLUMSTHE URBAN DIVIDE AND MACHINE LEARNINGGLCM (Gray Level Co-Occurrence Matrix) - Example MumbaiTHE URBAN DIVIDE - DEEP LEARNING APPROACHDeep learning methods such as Convolutional Neural Networks can automatically learn spatial features from the input image.Mboga, Persello, Bergado, Stein, “Detection of Informal Settlements from VHR Satellite Images using Convolutional Neural Networks, IGARSS 2017.DEGREE OF DEPRIVATION USING CNNSSource: A. Ajami et al. forthcoming Producers, uses and users Incorporating different slum development stages, dynamics and typologies? Feature selection – training – assessment – which algorithms and reference data? Transferability of methodology (temporal – spatial)? How to upscale to global level? Suitable data (spatial resolution, cost…)PROSPECTS FOR GLOBAL SLUM MAPPING?PRODUCERS, USES AND USER NEEDSBuilding model Slum mappers: government, researchers, communities, NGOs Better understanding user requirements – bridge communication gap  Making products relevant to support user needs Co-production of slum maps and data  Data access, distribution and maintenance (slum mapping as a social-technical infrastructure)TEMPORAL DYNAMICSEmergence and Growth of a slum in Huidi, Bangalore (marked with a red polygon). a) Slums emerge near aconstruction Site in 2008. b) Slum grows near the same site. c) Slum disappear when construction is complete in2013. d) A slum re-emerge at the same site in 2014 (Images– Google Earth) (Source: Dynaslum)https://www.tandfonline.com/doi/full/10.1080/22797254.2018.1535838Ranguelova et al. 201712345  Vacant land                               S C  O  OC SS STime Vacant landFormalInformalUNCERTAINTIES IN THE REFERENCE DATAIn area with higher agreement shows (on the ground): poor building materials, high density and located in the riverbankMisclassifications: high density and have a roof from asbestos, but not a slumSource: Pratomo et al., 2017:https://www.mdpi.com/2072-4292/9/11/1164Opportunity to link to NGOs and communitiesslum dweller groupsUNDERSTAND BETTER ENVIRONMENTAL CONDITIONS OF SLUMS: HAZARDS – CLIMATE WANG, J., Sliuzas, R., Kuffer, M., Kohli, D. https://www.sciencedirect.com/science/article/pii/S0048969718337811GOING AHEAD: CAN MAP SLUMS WITH CNNS BASED ON LIMITED TRAINING DATA Mapping small clusters of slums with training based on few large slumsGOING AHEAD: CNNS NEED TO HAVE TRAINING DATA THAT INCLUDE THE VARIATIONS CNNs need to be trained based on the full variety of their morphologiesUNCERTAINTIES ON SLUM BOUNDARIES: BANDUNG, INDONESIALocal authorities Ground-truth delineation including image MOST SUITABLE SPATIAL RESOLUTION OF IMAGESBenefits versus image and computational costsHOW CAN WE SHOW THE FUZZINESS IN MAPS Is the highest detail necessary? Ethical considerations (not) making data on slums publically available?SLUMS IN EUROPE? Immigrants in France. (L) Eviction from Calais, (R) New settlements in ParisINFORMATION NEEDS AND ETHIC CONSIDERATIONSShall we make slum maps and images publically available ???? https://www.sicherheitspolitik-blog.de/2018/07/11/the-digitalization-of-the-globe-machine-learning-about-population-in-need-of-support/Source Gevaert et al. 2018: https://www.mdpi.com/2220-9964/7/3/91POSSIBLE ETHICAL CONCERNS IN SLUM MAPPING Who decides and who owns the process? Who is eligible for compensation and resettlement? Who pays?  Issues of possible eviction or economic displacement – gentrification? …..SLUM EVICTION IN AHMEDABAD INDIALEADS TO FURTHER DEPRIVATION RELATED MOSTLY TO SERVICE LEVELS AND LOCATION OF NEW SITESMany residents do not qualifyVery poor temporary resettlementFinal settlement lacks qualityPatel, S., Sliuzas, R., & Mathur, N. (2015). http://doi.org/10.1177/0956247815569128SOME KEY ISSUES AND QUESTIONS  Definitions: do we really have a global definition? Slums are often not binary (slum vs non-slum) How do we bring in hazards in an effective manner (also non-binary, dynamic and related to  Diversity Should we differentiate at regional, country or city level?  At least we will need to include training sets that reflect diversity What do slum development processes imply for training samples and processing?  This is shown on the slides 4&5 – we need to include different development stages –but this makes the analysis complex!  How to connect local actors and communities (SDI etc.)? In data collection efforts for sample generation?  In validation of slum classification maps? As users of the data in daily management and upgrading, etc.?SOME KEY ISSUES AND QUESTIONS  Uses and users: Which potential uses have priority and for whom? Will political and other actors be prepared to accept and use such data sets derived from advanced image analysis?  What are the margins for error and will these be context dependent? Technical Image availability and sensor types Computational power – which processing facilities can support the level of computation required for this task and can these be accessed as and when needed? How to best connect to socio-economic datasets (Census, DHS, MICS etc.) Ethical and privacy issues Social-technical: what would an inclusive global slum mapping infrastructure look like and how to build and maintain it?NEW INITIATIVESOpportunities SDG process MAUPP partners and follow-up projects Group on Earth Observation – Human Planet Initiative (https://www.earthobservations.org/index.php https://www.itc.nl/hpi-forum/) Global programmes related to hazards and climate change (UNISDR, UNFCC) UN-HABITAT - GUO, Slum Upgrading Programme, Climate Change Unit: Building the Climate Resilience of the Urban Poor Initiative for UN Summit 2019Source: Ralf Graf. RxAxLxF Informal City  SOME USEFUL REFERENCES Gevaert, C. M., Sliuzas, R., Persello, C., & Vosselman, G. (2018). Evaluating the societal impact of using drones to support urban upgrading projects. ISPRS International Journal of Geo-Information, 7(3). https://doi.org/10.3390/ijgi7030091 Kuffer, M., Wang, J., Nagenborg, M., Pfeffer, K., Kohli, D., Sliuz, … Persello, C. (2018). The Scope of Earth-Observation to improve the consistency of the SDG slum indicator. International Journal of Geo-Information, 7(428), 1–28. https://doi.org/10.3390/ijgi7110428 Kuffer, M., Pfeffer, K., & Sliuzas, R. (2016). Slums from space-15 years of slum mapping using remote sensing. Remote Sensing. https://doi.org/10.3390/rs8060455 Kohli, D., Sliuzas, R., Kerle, N., & Stein, A. (2012). An ontology of slums for image-based classification. Computers, Environment and Urban Systems, 36(2), 154–163. Mahabir, R., Croitoru, A., Crooks, A. T., Agouris, P., & Stefanidis, A. (2018). A Critical Review of High and Very High-Resolution Remote Sensing Approaches for Detecting and Mapping Slums: Trends, Challenges and Emerging Opportunities. Urban Science, 2(8), 1–38. https://doi.org/10.3390/urbansci2010008

Prospects for global monitoring of the SDG SLUM indicator with earth observation:powerpoint

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Prospects for global monitoring of the SDG SLUM indicator with earth observation: powerpoint

Prospects for global monitoring of the SDG SLUM indicator with earth observation:powerpoint

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